def logarytm(x):
    for i in range(0, x.size):
        if x[i] != 0:
            x[i] = log(x[i])
    return x

T = 1
Fs = 10000
t = arange(0,T,1/Fs)

#Tworzymy wykresy
fig,ax = subplots(10, 4, figsize=(20,50))

#Generujemy sygnał
y = sin(2*pi*999.5*t)
ax[0,0].plot(t,y)
ax[0,0].set_title('Oryginalny sygnał')
ax[0,0].set_xlim(0,0.01)

#Obliczamy jego FFT
Y = fft.fft(y)
f = linspace(0,Fs,Y.size)
ax[0,2].plot(f,abs(Y))
ax[0,2].set_title('FFT sygnału')
ax[0,2].set_xlim(990,1010)
ax[0,3].plot(f,logarytm(abs(Y)))

########################## BARTLETT ##########################
h = bartlett(y.size)
ax[1,0].plot(t,h)
ax[1,0].set_title('Bartlett')

ny = h * y
Y = fft.fft(ny)
f = linspace(0,Fs,Y.size)
H = fft.fft(h)
ax[1,1].plot(f, logarytm(abs(H)))
ax[1,1].set_title('FFT Bartlett')
ax[1,2].plot(f,abs(Y))
ax[1,2].set_xlim(990,1010)
ax[1,3].plot(f,logarytm(abs(Y)))

########################## BLACKMAN ##########################
h = blackman(y.size)
ax[2,0].plot(t,h)
ax[2,0].set_title('Blackman')

ny = h * y
Y = fft.fft(ny)
f = linspace(0,Fs,Y.size)
H = fft.fft(h)
ax[2,1].plot(f, logarytm(abs(H)))
ax[2,1].set_title('FFT Blackman')
ax[2,2].plot(f,abs(Y))
ax[2,2].set_xlim(990,1010)
ax[2,3].plot(f,logarytm(abs(Y)))

########################## HAMMING ##########################
h = hamming(y.size)
ax[3,0].plot(t,h)
ax[3,0].set_title('Hamming')

ny = h * y
Y = fft.fft(ny)
f = linspace(0,Fs,Y.size)
H = fft.fft(h)
ax[3,1].plot(f, logarytm(abs(H)))
ax[3,1].set_title('FFT Hamming')
ax[3,2].plot(f,abs(Y))
ax[3,2].set_xlim(990,1010)
ax[3,3].plot(f,logarytm(abs(Y)))

########################## HANNING ##########################
h = hanning(y.size)
ax[4,0].plot(t,h)
ax[4,0].set_title('Hanning')

ny = h * y
Y = fft.fft(ny)
f = linspace(0,Fs,Y.size)
H = fft.fft(h)
ax[4,1].plot(f, logarytm(abs(H)))
ax[4,1].set_title('FFT Hanning')
ax[4,2].plot(f,abs(Y))
ax[4,2].set_xlim(990,1010)
ax[4,3].plot(f,logarytm(abs(Y)))

########################## KAISER ##########################
ks = [0, 5, 6, 8.6, 14]

for i in range(0, 5):
    h = kaiser(y.size, ks[i])
    ax[5 + i, 0].plot(t,h)
    ax[5 + i, 0].set_title('Kaiser %.1f' % (ks[i]))

    ny = h * y
    Y = fft.fft(ny)
    f = linspace(0,Fs,Y.size)
    H = fft.fft(h)
    ax[5 + i, 1].plot(f, logarytm(abs(H)))
    ax[5 + i, 1].set_title('FFT Kaiser %.1f' % (ks[i]))
    ax[5 + i, 2].plot(f,abs(Y))
    ax[5 + i, 2].set_xlim(990,1010)
    ax[5 + i, 3].plot(f,logarytm(abs(Y)))